A bottom-up spatial pattern of Earth system interactions

The intricate interplay of the Earth system’s biophysical processes provides the basis for Earth resilience and human wellbeing. While this interplay has been systematically studied on a global scale, a better understanding of the sub-global interactions is crucial in order to fully assess the systemic environmental impact of human activities.       
Building on the quantitative framework provided by the Earth system impact metric (Lade et al. 2021), we present a bottom-up spatial pattern of cross-scale Earth system interactions. In this study, we focus on the processes of change in carbon dioxide concentration, vegetation cover, and surface water runoff. These processes lie at the critical interface between human pressures and the major Earth system components of climate, land, and water. Interactions are quantified using the spatially resolved dynamical global vegetation model LPJmL (Lund-Potsdam-Jena managed Land). A comparison of the resulting spatial patterns to established climate- and vegetation-based divisions of the Earth reveals that parts of the patterns are already explained by the simple combination of vegetation types being naturally prevalent in an area. The effects of climate change on runoff are for example particularly high in areas originally covered by cool seasonal grasses only. In contrast, the effects of changes in vegetation cover on climate more closely follow the Köppen-Geiger climate classification, showing a particularly high interaction strength under tropical rainforest climate. Eventually, we derive an integrative world map of interaction zones using multivariate spatially constrained clustering.       
With this study, we provide a refined local assessment of cross-scale interactions between three crucial Earth system processes. By aggregating the results into larger regions, we aim to facilitate its applicability in decision support and communication.

Steven J Lade et al., A prototype Earth system impact metric that accounts for cross-scale interactions, Environ. Res. Lett. 16 115005 (2021).